docs: def precision_pct_pred_pos_curve(self, interval=False, delta_tau=0.001):
          """ Computes the relationship between precision
          and the percent of positively classified datapoints . """
          # compute thresholds based on the sorted probabilities
          orig_thresh = self.threshold
          sorted_labels, sorted_probs = self.sorted_values
  
          precisions = []
          pct_pred_pos = []
          taus = []
          tau = 0
          if not interval:
              for k in range(len(sorted_labels)):
                  # compute new accuracy
                  self.threshold = tau
                  precisions.append(self.precision)
                  pct_pred_pos.append(self.pct_pred_pos)
                  taus.append(tau)
                  
                  # update threshold
                  tau = sorted_probs[k]
  
          else:
              while tau < 1.0:
                  # compute new accuracy
                  self.threshold = tau
                  precisions.append(self.precision)
                  pct_pred_pos.append(self.pct_pred_pos)
                  taus.append(tau)
                  
                  # update threshold
                  tau += delta_tau
  
          # add last datapoint
          tau = 1.0
          self.threshold = tau
          precisions.append(self.precision)
          pct_pred_pos.append(self.pct_pred_pos)
          taus.append(tau)
  
          precisions.append(1.0)
          pct_pred_pos.append(0.0)
          taus.append(1.0 + 1e-12)
  
          self.threshold = orig_thresh
          return precisions, pct_pred_pos, taus